Modern X-ray systems, in particular modern C-arm X-ray systems having flat-panel detectors have now become established as part of standard practice in medical imaging, in particular also in interventional medical imaging. In addition to traditional projection imaging (radiography/fluoroscopy) these systems also support a mode similar to computed tomography in which a sequence of two-dimensional projection images from a sufficiently large number of different projection directions (which consequently describe a specific recording geometry) is converted into a three-dimensional image dataset. For example, the projection images can be recorded during a rotary movement of the on which an X-ray tube assembly and a detector are disposed opposite each other.
By means of such a 3D mode it is possible to reconstruct from a single rotation datasets which cover a large region of an object, for example a complete human cranium, and which offer a high spatial resolution in particular in comparison with diagnostic computed tomography. It is, however, disadvantageous that compared with conventional computed tomography the datasets have a lower contrast resolution and a lower contrast-to-noise ratio which for example may not be sufficient to preclude cerebral hemorrhages with certainty. Cerebral hemorrhages constitute a structure having an extremely low contrast which can be resolved only with difficulty by means of the C-arm X-ray apparatuses.
In three-dimensional C-arm imaging, as already described, the data recording consists in most cases, and in particular also in low-contrast applications, of a single rotary movement around the patient or, as the case may be, the object that is to be recorded. In order to improve the three-dimensional image quality in respect of the low contrasts several methods have hitherto been proposed in the prior art in order to improve the image quality.
Thus, noise reduction methods have been used both on the projection data and in the reconstructed image volume, for example noise reduction of the projection data at the same time as edge enhancement by means of bilateral filters or median filtering or noise reduction in the reconstructed image volume by means of non-linear filtering, for example median filters.
Another approach has been imported from the field of computed tomography and applied also to the three-dimensional reconstruction in C-arm X-ray apparatuses, namely the separation of the recorded projection images into disjoint subsets and the reconstruction of reconstruction datasets from in each case one of said subsets. The partial results are subsequently combined non-linearly to form a quality-enhanced image volume, an efficient approach relating to a wavelet-based fusion of two separately reconstructed datasets by means of correlation analysis; cf. in this regard for example the article by A. Borsdorf et al, “Separate CT Reconstruction for 3D Wavelet Based Noise Reduction Using Correlation Analysis”, in Yu, Bo (Eds.), IEEE NSS/MIC Conference Record (WEE Nuclear Science Symposium and Medical Imaging Conference, Honolulu, USA, Oct. 27-Nov. 3, 2007), 2007, pages 2633 to 2638.
DE 10 2006 041 033 A1 relates to a method for reconstructing a three-dimensional image volume by means of a virtual extension of the X-ray detector. In the examination of certain body regions a specified maximum width can be exceeded. For this purpose it is proposed to record two or more individual projection images at each curve plot-point of the trajectory, which images can be assembled into an extended projection image. The same recording geometry is therefore not present. The images must be different in terms of their recording regions to enable a virtual extension of the X-ray detector to be possible at all.
However, a disadvantage of these methods is that contrasts that are lost in individual projection images cannot be reinstated either by operations in the projection image or by operations in the image space.